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    Deep Learning AMI DLAMI Ubuntu 18.04 LTS | Support by SupportedImages

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    AWS Free Tier
    This product has charges associated with it for seller support. The Deep Learning AMI DLAMI Ubuntu 18.04 LTS is a powerful and flexible Amazon Machine Image designed for deep learning and AI development in the cloud. Pre-configured with popular frameworks such as TensorFlow, PyTorch, and MXNet, this AMI enables developers to streamline their machine learning workflows. It supports GPU instances for accelerated performance, making it ideal for training complex models quickly. With extensive documentation and community support, users can easily deploy and manage their deep learning applications. Suitable for data scientists, researchers, and developers, this AMI accelerates experimentation and innovation in machine learning projects, providing a robust environment to tackle various data-driven challenges effectively. Leverage the power of AWS to scale your AI initiatives with ease.
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    Deep Learning AMI DLAMI Ubuntu 18.04 LTS | Support by SupportedImages

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    Overview

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    This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.

    The Deep Learning AMI (DLAMI) based on Ubuntu 18.04 LTS provides a robust environment tailored specifically for deep learning practitioners and researchers. This AMI comes pre-installed with a comprehensive suite of popular machine learning frameworks such as TensorFlow, PyTorch, and MXNet, allowing you to accelerate your development and experimentation on AWS.

    Key Features:

    • Pre-Configured Frameworks: Save time with a host of deep learning frameworks already set up and ready for immediate use.
    • GPU Support: Leverage the power of NVIDIA GPUs to significantly enhance training speed for complex models.
    • Scalability: Seamlessly scale from a single instance to a multi-node setup to accommodate extensive datasets and model training.
    • Optimized for Performance: The AMI includes optimizations for performance, ensuring efficient utilization of resources for deep learning tasks.
    • Regular Updates: Stay current with the latest advancements in machine learning and deep learning models, libraries, and tools.

    Use Cases:

    • Model Training: Ideal for researchers and developers looking to train state-of-the-art neural networks on large datasets.
    • Experimentation: Experiment with various architectures and algorithms in a well-configured environment without deep system administration overhead.
    • Data Science Workflows: Enhance your data science projects with powerful computing resources tailored to handle heavy computation and large-scale data processing tasks.
    • Prototyping and Development: Quickly prototype and develop new models, leveraging AWS cloud infrastructure for easy collaboration and sharing.

    Utilize the Deep Learning AMI DLAMI Ubuntu 18 to enhance your machine learning projects and gain a competitive edge in your research or development efforts. Get started today and unlock the full potential of deep learning on AWS!

    Try our most popular AMIs on AWS EC2

    Highlights

    • The Deep Learning AMI DLAMI Ubuntu 18.04 LTS is designed specifically for developers and data scientists seeking to leverage advanced machine learning capabilities. This AMI comes pre-installed with popular deep learning frameworks such as TensorFlow, PyTorch, and Apache MXNet, allowing users to quickly set up robust training environments. With optimized libraries and tools, users can effectively accelerate model training and deployment for various applications.
    • Security and updates are critical for any cloud deployment, and the DLAMI Ubuntu 18 includes the latest security patches and timely updates. By using this AMI, organizations benefit from a secure operating environment designed for production workloads, ensuring that critical data and intellectual property remain protected. Users also gain access to AWS support resources tailored for deep learning aspirations.
    • The potential use cases for the Deep Learning AMI DLAMI Ubuntu 18 are extensive, ranging from image and speech recognition to natural language processing and autonomous systems. Researchers and enterprises can harness the power of AWS's scalable infrastructure to develop, test, and fine-tune their machine learning models. With the flexibility of EC2, users can easily scale their deployments to accommodate varying workloads and operational demands.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 18.04 LTS

    Typical total price

    This estimate is based on use of the seller's recommended configuration (inf1.6xlarge) in the US East (N. Virginia) Region. View pricing details

    $2.30/hour

    Pricing

    Deep Learning AMI DLAMI Ubuntu 18.04 LTS | Support by SupportedImages

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covering your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (599)

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    • ...
    Instance type
    Product cost/hour
    EC2 cost/hour
    Total/hour
    t1.micro
    $0.07
    $0.02
    $0.09
    t2.nano
    $0.07
    $0.006
    $0.076
    t2.micro
    AWS Free Tier
    $0.21
    $0.012
    $0.222
    t2.small
    $0.07
    $0.023
    $0.093
    t2.medium
    $0.14
    $0.046
    $0.186
    t2.large
    $0.14
    $0.093
    $0.233
    t2.xlarge
    $0.28
    $0.186
    $0.466
    t2.2xlarge
    $0.56
    $0.371
    $0.931
    t3.nano
    $0.07
    $0.005
    $0.075
    t3.micro
    AWS Free Tier
    $0.07
    $0.01
    $0.08

    Additional AWS infrastructure costs

    Type
    Cost
    EBS General Purpose SSD (gp3) volumes
    $0.08/per GB/month of provisioned storage

    Vendor refund policy

    The instance can be terminated at anytime to stop incurring charges

    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

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    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    System Updates

    Additional details

    Usage instructions

    SSH to the instance and login as 'ubuntu' using the key specified at launch.

    OS commands via SSH: SSH as user 'ubuntu' to the running instance and use sudo to run commands requiring root access.

    More on using Deep Learning AMI with Conda: https://docs.aws.amazon.com/dlami/latest/devguide/tutorial-conda.html 

    Support

    Vendor support

    Email support for this AMI is available through the following: https://supportedimages.com/support/  OR support@supportedimages.com 

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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    Ratings and reviews

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    1 AWS reviews
    jdinca

    Old Tensorflow and unable to use GPUs

    Reviewed on Aug 12, 2022
    Purchase verified by AWS

    Applied all standard good practices, GPUs are visible, but the install pushed everything to CPUs.
    Also, old version of tensorflow. Didn't bother updating just moved to another instance.

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